M. C. Vidal

ANOCVA in R: A Software to Compare Clusters between Groups and Its Application to the Study of Autism Spectrum Disorder

J. Sato, A. Fujita, D. Takahashi, 2017, Front. Neurosci..

Identification of alterations associated with age in the clustering structure of functional brain networks

Grover E. C. Guzman, J. Sato, A. Fujita, 2018, PloS one.

Exploring a targeted approach for public health capacity restrictions during COVID-19 using a new computational model

T. Ye, R. Martin, B. Tam, 2022, medRxiv.

Complex Network Measures in Autism Spectrum Disorders

João Ricardo Sato, Suzana de Siqueira Santos, André Fujita, 2018, IEEE/ACM Transactions on Computational Biology and Bioinformatics.

ANOCVA: A Nonparametric Statistical Test to Compare Clustering Structures

André Fujita, Alexandre G. Patriota, Maciel Calebe Vidal, 2018 .

Identification of segregated regions in the functional brain connectome of autistic patients by a combination of fuzzy spectral clustering and entropy analysis.

João Ricardo Sato, André Fujita, Maciel Calebe Vidal, 2016, Journal of psychiatry & neuroscience : JPN.

Granger Causality among Graphs and Application to Functional Brain Connectivity in Autism Spectrum Disorder

João Ricardo Sato, André Fujita, Maciel Calebe Vidal, 2021, Entropy.

A Statistical Method to Distinguish Functional Brain Networks

Daniel Y. Takahashi, André Fujita, Maciel C. Vidal, 2017, Front. Neurosci..

Correlation between graphs with an application to brain networks analysis

João Ricardo Sato, Daniel Y. Takahashi, André Fujita, 2015, 1512.06830.

Correlation between graphs with an application to brain network analysis

J. Balardin, M. C. Vidal, André Fujita, 2017, Comput. Stat. Data Anal..

Identification of segregated regions in the functional brain connectome of autistic patients by a combination of fuzzy spectral clustering and entropy analysis.

J. Sato, J. Balardin, M. C. Vidal, 2016, Journal of psychiatry & neuroscience : JPN.